Managing Complexity and Uncertainty in Natural and Socio-Ecological Systems


I wrote most of this as an internal document for a Regional Council in 2009 when it was apparent that both the internal management style and the approach to the wider natural systems and communities was not conducive to long term success.  Updated a tad.  Some very good people, but I’d argue that the greatest barriers to achievement are not any problems with ‘human resources’ (oh, how I hate that term – it sets up the various mechanical structures I write about here) but rather the barrier, or conduit to success, relates to the concepts that predominate in our collective heads; or –  in George Lakoff’s term – The Metaphors we Live by.  We tend to function in Zone A, when we should actually be functioning in Zone C.

If uncertainty calls for learning and adjustment, the need for adaptive management seems indisputable. The elements of adaptive management—monitoring, feedback, capacity to learn from past mistakes, and incentives to experiment with new adaptations—are rather obvious, though by no means simple to achieve (Ascher 2001).

Attempts to manage complex, dynamic, adaptive environmental systems as if they are regular and controllable has often lead to perverse outcomes and failure. This is especially the case where the approach is to structure a top-down, command-and-control, standardised, reductive, rigid, and universal solution extending to forests, fisheries, soil, water, whole landscapes, and their associated communities. This failure of regulation supported by what are presumed to be universal facts has been referred to as “The pathology of resource management”.

The essential problem arises from a number of assumptions:

  1. That a system is universally simple, linear, non-adaptive and predictable when many (if not most) parts of it are complex, non-linear, adaptive and unpredictable across space and time,
  2. That the issues can be defined wholly in the biophysical sense, without regard to cultural values, behaviours and adaptation (people are just another cog),
  3. That decision making is more about information and data than regionalised or localised judgement; the latter requiring an ability to connect the dots and judge within a given context,
  4. That knowledge is certain and held ‘up’ the hierarchy, with the learning and knowledge of local people largely irrelevant (they are there to be instructed, not having knowledge and judgement of their own, and having suspect motives)

The problem of dealing with complex environments by science, policy and management has lead to an increase in the search for alternative approaches. The established approaches of regulation (A) and incentivising “rational choice” through incentive structures (B) remain applicable in many contexts. To these are added approaches that increase the capacity to deal with complexity by systems of knowing, learning, adapting, buffering, and responding within environments that change in space and time (C). The diagram below is an adaptation of the work of G.D. Peterson.

image003

Approaches to managing natural & social systems with varying degrees of complexity. X-axis Increasing uncertainty, irregularity & unpredictability. Y-Axis Increasing complexity and uncontrollability

With distance from the certain and controllable to uncertain and uncontrollable, a shift in approach is required.  At their extremes, they represent two broad paradigms for conceptualising simple rule-driven hard systems (the physics of a billiard table) contrasted with complex adaptive soft systems (such as raising a child or solving global hunger).

They also represent two broad paradigms of conceptualising ‘sustainability’.  Within sustainability constructs, we shift from A. the more ordered ‘resource sufficiency‘ idea of sustainability (where the world is analogous to a mechanical sausage factory of inputs and outputs whose control guarantees sufficiency), to C. the ‘functional integrity‘ idea of sustainability where the more ‘organic’ system is subject to complex interrelationships that are constantly shifting and adapting).  B is an intermediate – ‘complicated’ systems such as getting a rocket to the moon and back, which, while complicated, also follow standard Newtonian physical laws.

Concepts of ‘scientific management’ of ‘resources’ clearly relate to ‘resource sufficiency’ approaches to natural systems (these natural systems are termed ‘resources’ with human elements marginalised or removed).  Arguably industrial forestry and agriculture (hard resourcism) are under the impression that certainty and controllability are the ruling conditions.   Their use of financial analysis to set strategy rather than to refine tactics within a strategy is highly indicative of faith in future certainty.  Arguably hardline preservation as the only conservation strategy (all human activity removed, except hiking) is the antithesis of industrial land use, working within the same conceptual framework.  Another example is the centralised military ideas of logistical warfare on the Western Front of World War I (Field Marshall Haig the best exemplar).

Applying such conceptual frameworks where the subject is indeed simple and controllable is not problematic.  The ‘pathology of resource management’ occurs where the subject is presumed to be certain and controllable, but is not (The Somme and various corporate failings being salutary lessons).

Concepts of ‘resilience theory’ and Elinor Ostrom’s management of the commons relate more to the ‘functional integrity’ concepts of how socio-ecological systems work.  The system is complex and uncertain, and acknowledgment of uncertainty, as well as inclusive of the values and adaptability of integrated social and natural systems (socio-ecological systems) are keys to maintaining the integrity of the system, even as it changes.

The philosophy of the two paradigms is further outlined in the table below.

Attributes of systemic and mechanistic approaches to see the natural & social world

Attribute

Mechanistic/Analytical

Systemic/Integrative
Philosophy Narrow & targeted

Disproof by experiment

Teleological/Deterministic

Broad & exploratory

Multiple lines of converging evidence

Indeterministic/Probabilistic

Perceived organisation Biotic interactions

Fixed environment

Single scale

Focus on components/entities

Biophysical interactions

Self-organisation

Multiple scales with cross-scale interactions

Focus on processes/relationships

Causation Single and separable Multiple and only partially separable
Uncertainty Eliminate (reject) uncertainty Incorporate (accept) uncertainty
Human-Nature relationship Culture separates Homo sapiens from nature – defiles and destroys ‘pristine’ nature Homo sapiens part of and embedded within Nature
Decision making From authority down Incorporating local knowledge

Partly sourced from Holling 1988 and Callicott et al. 1999

Without getting these philosophical concepts right, we are in danger of not just not achieving our potential, but of tipping ourselves over the edge with our hubris and our faith in certainty.  Where, one might ask, is the Western world’s appreciation of the tricksters of old polytheistic religion?

Placate the gods, or something bad may happen.  Which today would be better paraphrased as “Expect uncertainty and prepare for it, or something will bite back.”

Bibliography

Agrawal, A., 2005. Environmentality: technologies of government and the making of subjects. Durham: Duke University Press.

Ascher, W., 2001. Coping with Complexity and Organizational Interests in Natural Resource Management. Ecosystems. 4: 742–757

Callicott, J. B., L. B. Crowder, & K. Mumford. 1999. Current normative concepts in conservation. Conservation Biology 13(1):22-35

Funtowicz, S.O. & J.R. Ravetz, 1993. Science for the Post-Normal Age. Futures 25 (7): 735–755.

Grove, T. L. & C. A. Edwards., 1993. Do we need a new developmental paradigm? Agriculture, Ecosystems and Environment, 46, 135-145

Holling, C. S. & G. K. Meffe, 1996. Command and Control and the Pathology of Natural Resource Management. Conservation Biology, 10, 328-337.

Holling, C. S. 1998. Two cultures of ecology. Conservation Ecology [online] 2(2): 4. Available from http://www.consecol.org/vol2/iss2/art4

Peterson, G.D., Cumming, G.S., & S.R. Carpenter, 2003. Scenario Planning: a Tool for Conservation in an Uncertain World. Conservation Biology. 17(2): 358–366

Peterson, G.D., Carpenter, S. R. & W. A. Brock, 2003. Uncertainty and the Management of Multistate Ecosystems: an Apparently Rational Route to Collapse. Ecology 84(6): 1403–1411

Peterson G. D. 2004. Ecological Management, Control, Uncertainty, and Understanding. In Ecosystem Ecology

Plumwood, V. 2002. Environmental Culture: the ecological crisis of reason. Routledge.

Ralston Saul, J. 1992. Voltaire’s Bastards: The dictatorship of reason in the west. London: Sinclair Stevenson.

Ravetz, J.R. 2007. Post-Normal Science and the complexity of transitions towards sustainability. Ecological Complexity 3

Scott, J. C. 1998., Seeing like a state: how certain schemes to improve the human condition have failed. New Haven: Yale University Press.

Shiva, V. 1993. Monocultures of the mind: perspective on biodiversity and biotechnology. New Delhi: Natraj Publishers.

Thompson, P.B. 2007.  Agricultural sustainability: what it is and what it is not.  Int. J of Agricultural Sustainability 5(1): 5-16

Tognetti, S.S. 1999. Science in a double-bind: Gregory Bateson and the origins of post-normal science. Futures 31: 689–703

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